Multilevel Attention Networks for Synthetic Aperture Radar Automatic Target Recognition-Reference-Cited by-同舟云学术

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Multilevel Attention Networks for Synthetic Aperture Radar Automatic Target Recognition

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Guo Yuxia¹,Zeng Zhiqiang²^ORCID,Jin Mingming³,Sun Jinping³^ORCID,Meng Zhongjie¹^ORCID,Hong Wen⁴^ORCID

Affiliation:

1. School of Astronautics, Northwestern Polytechnical University, Xi’an, China

2. Beijing Institute of Remote Sensing Equipment, Beijing, China

3. School of Electronic and Information Engineering, Beihang University, Beijing, China

4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8859/10365397/10565863.pdf?arnumber=10565863

Reference15 articles.

1. Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives

2. SAR ATR Using Complex-Valued CNN

3. Few-Shot SAR Target Recognition Through Meta-Adaptive Hyperparameters Learning for Fast Adaptation

4. Target Classification Using the Deep Convolutional Networks for SAR Images

5. Lightweight Two-Stream Convolutional Neural Network for SAR Target Recognition

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